Method and system for measuring spasticity

Abstract

A method for measuring spasticity is provided and includes: obtaining sensing signals corresponding to a limb movement through at least one sensor during a period of time; transforming the sensing signals into a two-dimensional image; and inputting the two-dimensional image into a convolutional neural network to output a spasticity determination result.

What is claimed is: 
     
       1. A method for measuring spasticity, comprising:
 obtaining, by a at least one sensor, at least one sensing signal corresponding to a limb movement during a time period; 
 transforming the at least one sensing signal into a two-dimensional image; and 
 inputting the two-dimensional image into a convolutional neural network to output a spasticity determination result, 
 wherein the at least one sensor comprises an inertial sensor, the at least one sensing signal comprises a plurality of acceleration signals, and the step of transforming the at least one sensing signal into the two-dimensional image comprises: 
 generating the two-dimensional image according to a following equation (1):
     I   i,j =diff( a   1,i   ,a   2,j )  (1)
 
 
 wherein I i,j  denotes a grey level at i th  column and j th  raw of the two-dimensional image, a 1,i  denotes a value of one of the acceleration signals at a time point i, a 2,j  denotes a value or another one of the acceleration signals at a time point j, and diff( ) is a difference function for two values. 
 
     
     
       2. The method of  claim 1 , wherein the at least one sensor further comprises an electromyography sensor, or a pressure sensor. 
     
     
       3. The method of  claim 1 , wherein the difference function diff( ) is written as a following equation (2):
   diff( a   1,i   ,a   2,j )= c   1   ×|a   1,i   −a   2,j   |+c   2 ×|( a   1,i+1   −a   1,i−1 )−( a   2,j+1   −a   2,j−1 )|  (2)
 
 wherein c 1 , c 2  are constants. 
 
     
     
       4. A system for measuring spasticity, comprising:
 at least one sensor, configured to obtain at least one sensing signal corresponding to a limb movement during a time period; and 
 a computation circuit coupled to the at least one sensor and configured to transform the at least one sensing signal into a two-dimensional image, and input the two-dimensional image into a convolutional neural network to output a spasticity determination result, 
 wherein the at least one sensor comprises an inertial sensor, and the at least one sensing signal comprises a plurality of acceleration signals, 
 wherein the computation circuit is configured to generate the two-dimensional image according to a following equation (1):
     I   i,j =diff( a   1,i   ,a   2,j )  (1)
 
 
 wherein I i,j  denotes a grey level at i th  column and j th  raw of the two-dimensional image, a 1,i  denotes a value of one of the acceleration signals at a time point i, a 2,j  denotes a value or another one of the acceleration signals at a time point j, diff( ) is a difference function for two values. 
 
     
     
       5. The system of  claim 4 , wherein the at least one sensor further comprises an electromyography sensor, or a pressure sensor. 
     
     
       6. The system of  claim 4 , wherein the difference function diff( ) is written as a following equation (2):
   diff( a   1,i   ,a   2,j )= c   1   ×|a   1,i   −a   2,j   |+c   2 ×|( a   1,i+1   −a   1,i−1 )−( a   2,j+1   −a   2,j−1 )|  (2)
 
 wherein c 1 , c 2  are constants.